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The repeated median line estimator is a highly robust method for fitting a regression line to a set of n data points in the plane. In this paper, we consider the problem of updating the estimate after a point is removed from or added to the data set. This problem occurs e.g. in statistical...
Persistent link: https://www.econbiz.de/10009770914
Standard median filters preserve abrupt shifts (edges) and remove impulsive noise (outliers) from a constant signal but they deteriorate in trend periods. FIR median hybrid (FMH) filters are more flexible and also preserve shifts, but they are much more vulnerable to outliers. Application of...
Persistent link: https://www.econbiz.de/10010516929
Principal Component Analysis (PCA) is very sensitive in presence of outliers. One of the most appealing robust methods for principal component analysis uses the Projection-Pursuit principle. Here, one projects the data on a lower-dimensional space such that a robust measure of variance of the...
Persistent link: https://www.econbiz.de/10014052385
The L1-median is a robust estimator of multivariate location with good statistical properties. Several algorithms for computing the L1-median are available. Problem specific algorithms can be used, but also general optimization routines. The aim is to compare different algorithms with respect to...
Persistent link: https://www.econbiz.de/10013137216
Persistent link: https://www.econbiz.de/10008664195
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The L1-median is a robust estimator of multivariate location with good statistical properties. Several algorithms for computing the L1- median are available. Problem speci c algorithms can be used, but also general optimization routines. The aim is to compare dierent algorithms with respect to...
Persistent link: https://www.econbiz.de/10011091113
The L <Subscript>1</Subscript>-median is a robust estimator of multivariate location with good statistical properties. Several algorithms for computing the L <Subscript>1</Subscript>-median are available. Problem specific algorithms can be used, but also general optimization routines. The aim is to compare different algorithms with respect...</subscript></subscript>
Persistent link: https://www.econbiz.de/10010998479
We study a group lasso estimator for the multivariate linear regression model that accounts for correlated error terms. A block coordinate descent algorithm is used to compute this estimator. We perform a simulation study with categorical data and multivariate time series data, typical settings...
Persistent link: https://www.econbiz.de/10013010637